27.257 299 999 999 997 95 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 27.257 299 999 999 997 95(10) to 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

What are the steps to convert decimal number
27.257 299 999 999 997 95(10) to 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. First, convert to binary (in base 2) the integer part: 27.
Divide the number repeatedly by 2.

Keep track of each remainder.

We stop when we get a quotient that is equal to zero.


  • division = quotient + remainder;
  • 27 ÷ 2 = 13 + 1;
  • 13 ÷ 2 = 6 + 1;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the integer part of the number.

Take all the remainders starting from the bottom of the list constructed above.

27(10) =


1 1011(2)


3. Convert to binary (base 2) the fractional part: 0.257 299 999 999 997 95.

Multiply it repeatedly by 2.


Keep track of each integer part of the results.


Stop when we get a fractional part that is equal to zero.


  • #) multiplying = integer + fractional part;
  • 1) 0.257 299 999 999 997 95 × 2 = 0 + 0.514 599 999 999 995 9;
  • 2) 0.514 599 999 999 995 9 × 2 = 1 + 0.029 199 999 999 991 8;
  • 3) 0.029 199 999 999 991 8 × 2 = 0 + 0.058 399 999 999 983 6;
  • 4) 0.058 399 999 999 983 6 × 2 = 0 + 0.116 799 999 999 967 2;
  • 5) 0.116 799 999 999 967 2 × 2 = 0 + 0.233 599 999 999 934 4;
  • 6) 0.233 599 999 999 934 4 × 2 = 0 + 0.467 199 999 999 868 8;
  • 7) 0.467 199 999 999 868 8 × 2 = 0 + 0.934 399 999 999 737 6;
  • 8) 0.934 399 999 999 737 6 × 2 = 1 + 0.868 799 999 999 475 2;
  • 9) 0.868 799 999 999 475 2 × 2 = 1 + 0.737 599 999 998 950 4;
  • 10) 0.737 599 999 998 950 4 × 2 = 1 + 0.475 199 999 997 900 8;
  • 11) 0.475 199 999 997 900 8 × 2 = 0 + 0.950 399 999 995 801 6;
  • 12) 0.950 399 999 995 801 6 × 2 = 1 + 0.900 799 999 991 603 2;
  • 13) 0.900 799 999 991 603 2 × 2 = 1 + 0.801 599 999 983 206 4;
  • 14) 0.801 599 999 983 206 4 × 2 = 1 + 0.603 199 999 966 412 8;
  • 15) 0.603 199 999 966 412 8 × 2 = 1 + 0.206 399 999 932 825 6;
  • 16) 0.206 399 999 932 825 6 × 2 = 0 + 0.412 799 999 865 651 2;
  • 17) 0.412 799 999 865 651 2 × 2 = 0 + 0.825 599 999 731 302 4;
  • 18) 0.825 599 999 731 302 4 × 2 = 1 + 0.651 199 999 462 604 8;
  • 19) 0.651 199 999 462 604 8 × 2 = 1 + 0.302 399 998 925 209 6;
  • 20) 0.302 399 998 925 209 6 × 2 = 0 + 0.604 799 997 850 419 2;
  • 21) 0.604 799 997 850 419 2 × 2 = 1 + 0.209 599 995 700 838 4;
  • 22) 0.209 599 995 700 838 4 × 2 = 0 + 0.419 199 991 401 676 8;
  • 23) 0.419 199 991 401 676 8 × 2 = 0 + 0.838 399 982 803 353 6;
  • 24) 0.838 399 982 803 353 6 × 2 = 1 + 0.676 799 965 606 707 2;
  • 25) 0.676 799 965 606 707 2 × 2 = 1 + 0.353 599 931 213 414 4;
  • 26) 0.353 599 931 213 414 4 × 2 = 0 + 0.707 199 862 426 828 8;
  • 27) 0.707 199 862 426 828 8 × 2 = 1 + 0.414 399 724 853 657 6;
  • 28) 0.414 399 724 853 657 6 × 2 = 0 + 0.828 799 449 707 315 2;
  • 29) 0.828 799 449 707 315 2 × 2 = 1 + 0.657 598 899 414 630 4;
  • 30) 0.657 598 899 414 630 4 × 2 = 1 + 0.315 197 798 829 260 8;
  • 31) 0.315 197 798 829 260 8 × 2 = 0 + 0.630 395 597 658 521 6;
  • 32) 0.630 395 597 658 521 6 × 2 = 1 + 0.260 791 195 317 043 2;
  • 33) 0.260 791 195 317 043 2 × 2 = 0 + 0.521 582 390 634 086 4;
  • 34) 0.521 582 390 634 086 4 × 2 = 1 + 0.043 164 781 268 172 8;
  • 35) 0.043 164 781 268 172 8 × 2 = 0 + 0.086 329 562 536 345 6;
  • 36) 0.086 329 562 536 345 6 × 2 = 0 + 0.172 659 125 072 691 2;
  • 37) 0.172 659 125 072 691 2 × 2 = 0 + 0.345 318 250 145 382 4;
  • 38) 0.345 318 250 145 382 4 × 2 = 0 + 0.690 636 500 290 764 8;
  • 39) 0.690 636 500 290 764 8 × 2 = 1 + 0.381 273 000 581 529 6;
  • 40) 0.381 273 000 581 529 6 × 2 = 0 + 0.762 546 001 163 059 2;
  • 41) 0.762 546 001 163 059 2 × 2 = 1 + 0.525 092 002 326 118 4;
  • 42) 0.525 092 002 326 118 4 × 2 = 1 + 0.050 184 004 652 236 8;
  • 43) 0.050 184 004 652 236 8 × 2 = 0 + 0.100 368 009 304 473 6;
  • 44) 0.100 368 009 304 473 6 × 2 = 0 + 0.200 736 018 608 947 2;
  • 45) 0.200 736 018 608 947 2 × 2 = 0 + 0.401 472 037 217 894 4;
  • 46) 0.401 472 037 217 894 4 × 2 = 0 + 0.802 944 074 435 788 8;
  • 47) 0.802 944 074 435 788 8 × 2 = 1 + 0.605 888 148 871 577 6;
  • 48) 0.605 888 148 871 577 6 × 2 = 1 + 0.211 776 297 743 155 2;
  • 49) 0.211 776 297 743 155 2 × 2 = 0 + 0.423 552 595 486 310 4;
  • 50) 0.423 552 595 486 310 4 × 2 = 0 + 0.847 105 190 972 620 8;
  • 51) 0.847 105 190 972 620 8 × 2 = 1 + 0.694 210 381 945 241 6;
  • 52) 0.694 210 381 945 241 6 × 2 = 1 + 0.388 420 763 890 483 2;
  • 53) 0.388 420 763 890 483 2 × 2 = 0 + 0.776 841 527 780 966 4;

We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit) and at least one integer that was different from zero => FULL STOP (Losing precision - the converted number we get in the end will be just a very good approximation of the initial one).


4. Construct the base 2 representation of the fractional part of the number.

Take all the integer parts of the multiplying operations, starting from the top of the constructed list above:


0.257 299 999 999 997 95(10) =


0.0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0011 0(2)

5. Positive number before normalization:

27.257 299 999 999 997 95(10) =


1 1011.0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0011 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 4 positions to the left, so that only one non zero digit remains to the left of it:


27.257 299 999 999 997 95(10) =


1 1011.0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0011 0(2) =


1 1011.0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0011 0(2) × 20 =


1.1011 0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0011 0(2) × 24


7. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

Sign 0 (a positive number)


Exponent (unadjusted): 4


Mantissa (not normalized):
1.1011 0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0011 0


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


4 + 2(11-1) - 1 =


(4 + 1 023)(10) =


1 027(10)


9. Convert the adjusted exponent from the decimal (base 10) to 11 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 1 027 ÷ 2 = 513 + 1;
  • 513 ÷ 2 = 256 + 1;
  • 256 ÷ 2 = 128 + 0;
  • 128 ÷ 2 = 64 + 0;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

10. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1027(10) =


100 0000 0011(2)


11. Normalize the mantissa.

a) Remove the leading (the leftmost) bit, since it's allways 1, and the decimal point, if the case.


b) Adjust its length to 52 bits, by removing the excess bits, from the right (if any of the excess bits is set on 1, we are losing precision...).


Mantissa (normalized) =


1. 1011 0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0 0110 =


1011 0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011


12. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
0 (a positive number)


Exponent (11 bits) =
100 0000 0011


Mantissa (52 bits) =
1011 0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011


Decimal number 27.257 299 999 999 997 95 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0011 - 1011 0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011

How to convert numbers from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 64 bit double precision IEEE 754 binary floating point:

  • 1. If the number to be converted is negative, start with its the positive version.
  • 2. First convert the integer part. Divide repeatedly by 2 the positive representation of the integer number that is to be converted to binary, until we get a quotient that is equal to zero, keeping track of each remainder.
  • 3. Construct the base 2 representation of the positive integer part of the number, by taking all the remainders from the previous operations, starting from the bottom of the list constructed above. Thus, the last remainder of the divisions becomes the first symbol (the leftmost) of the base two number, while the first remainder becomes the last symbol (the rightmost).
  • 4. Then convert the fractional part. Multiply the number repeatedly by 2, until we get a fractional part that is equal to zero, keeping track of each integer part of the results.
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the multiplying operations, starting from the top of the list constructed above (they should appear in the binary representation, from left to right, in the order they have been calculated).
  • 6. Normalize the binary representation of the number, shifting the decimal mark (the decimal point) "n" positions either to the left, or to the right, so that only one non zero digit remains to the left of the decimal mark.
  • 7. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal mark, if the case) and adjust its length to 52 bits, either by removing the excess bits from the right (losing precision...) or by adding extra bits set on '0' to the right.
  • 9. Sign (it takes 1 bit) is either 1 for a negative or 0 for a positive number.

Example: convert the negative number -31.640 215 from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point:

  • 1. Start with the positive version of the number:

    |-31.640 215| = 31.640 215

  • 2. First convert the integer part, 31. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 31 ÷ 2 = 15 + 1;
    • 15 ÷ 2 = 7 + 1;
    • 7 ÷ 2 = 3 + 1;
    • 3 ÷ 2 = 1 + 1;
    • 1 ÷ 2 = 0 + 1;
    • We have encountered a quotient that is ZERO => FULL STOP
  • 3. Construct the base 2 representation of the integer part of the number by taking all the remainders of the previous dividing operations, starting from the bottom of the list constructed above:

    31(10) = 1 1111(2)

  • 4. Then, convert the fractional part, 0.640 215. Multiply repeatedly by 2, keeping track of each integer part of the results, until we get a fractional part that is equal to zero:
    • #) multiplying = integer + fractional part;
    • 1) 0.640 215 × 2 = 1 + 0.280 43;
    • 2) 0.280 43 × 2 = 0 + 0.560 86;
    • 3) 0.560 86 × 2 = 1 + 0.121 72;
    • 4) 0.121 72 × 2 = 0 + 0.243 44;
    • 5) 0.243 44 × 2 = 0 + 0.486 88;
    • 6) 0.486 88 × 2 = 0 + 0.973 76;
    • 7) 0.973 76 × 2 = 1 + 0.947 52;
    • 8) 0.947 52 × 2 = 1 + 0.895 04;
    • 9) 0.895 04 × 2 = 1 + 0.790 08;
    • 10) 0.790 08 × 2 = 1 + 0.580 16;
    • 11) 0.580 16 × 2 = 1 + 0.160 32;
    • 12) 0.160 32 × 2 = 0 + 0.320 64;
    • 13) 0.320 64 × 2 = 0 + 0.641 28;
    • 14) 0.641 28 × 2 = 1 + 0.282 56;
    • 15) 0.282 56 × 2 = 0 + 0.565 12;
    • 16) 0.565 12 × 2 = 1 + 0.130 24;
    • 17) 0.130 24 × 2 = 0 + 0.260 48;
    • 18) 0.260 48 × 2 = 0 + 0.520 96;
    • 19) 0.520 96 × 2 = 1 + 0.041 92;
    • 20) 0.041 92 × 2 = 0 + 0.083 84;
    • 21) 0.083 84 × 2 = 0 + 0.167 68;
    • 22) 0.167 68 × 2 = 0 + 0.335 36;
    • 23) 0.335 36 × 2 = 0 + 0.670 72;
    • 24) 0.670 72 × 2 = 1 + 0.341 44;
    • 25) 0.341 44 × 2 = 0 + 0.682 88;
    • 26) 0.682 88 × 2 = 1 + 0.365 76;
    • 27) 0.365 76 × 2 = 0 + 0.731 52;
    • 28) 0.731 52 × 2 = 1 + 0.463 04;
    • 29) 0.463 04 × 2 = 0 + 0.926 08;
    • 30) 0.926 08 × 2 = 1 + 0.852 16;
    • 31) 0.852 16 × 2 = 1 + 0.704 32;
    • 32) 0.704 32 × 2 = 1 + 0.408 64;
    • 33) 0.408 64 × 2 = 0 + 0.817 28;
    • 34) 0.817 28 × 2 = 1 + 0.634 56;
    • 35) 0.634 56 × 2 = 1 + 0.269 12;
    • 36) 0.269 12 × 2 = 0 + 0.538 24;
    • 37) 0.538 24 × 2 = 1 + 0.076 48;
    • 38) 0.076 48 × 2 = 0 + 0.152 96;
    • 39) 0.152 96 × 2 = 0 + 0.305 92;
    • 40) 0.305 92 × 2 = 0 + 0.611 84;
    • 41) 0.611 84 × 2 = 1 + 0.223 68;
    • 42) 0.223 68 × 2 = 0 + 0.447 36;
    • 43) 0.447 36 × 2 = 0 + 0.894 72;
    • 44) 0.894 72 × 2 = 1 + 0.789 44;
    • 45) 0.789 44 × 2 = 1 + 0.578 88;
    • 46) 0.578 88 × 2 = 1 + 0.157 76;
    • 47) 0.157 76 × 2 = 0 + 0.315 52;
    • 48) 0.315 52 × 2 = 0 + 0.631 04;
    • 49) 0.631 04 × 2 = 1 + 0.262 08;
    • 50) 0.262 08 × 2 = 0 + 0.524 16;
    • 51) 0.524 16 × 2 = 1 + 0.048 32;
    • 52) 0.048 32 × 2 = 0 + 0.096 64;
    • 53) 0.096 64 × 2 = 0 + 0.193 28;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 52) and at least one integer part that was different from zero => FULL STOP (losing precision...).
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the previous multiplying operations, starting from the top of the constructed list above:

    0.640 215(10) = 0.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 6. Summarizing - the positive number before normalization:

    31.640 215(10) = 1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 7. Normalize the binary representation of the number, shifting the decimal mark 4 positions to the left so that only one non-zero digit stays to the left of the decimal mark:

    31.640 215(10) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 20 =
    1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

  • 9. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as shown above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1 = (4 + 1023)(10) = 1027(10) =
    100 0000 0011(2)

  • 10. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign) and adjust its length to 52 bits, by removing the excess bits, from the right (losing precision...):

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

    Mantissa (normalized): 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Conclusion:

    Sign (1 bit) = 1 (a negative number)

    Exponent (8 bits) = 100 0000 0011

    Mantissa (52 bits) = 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Number -31.640 215, converted from decimal system (base 10) to 64 bit double precision IEEE 754 binary floating point =
    1 - 100 0000 0011 - 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100